电子垃圾的循环利用

电子垃圾成为当今面临的亟待解决的难题,用科学的发展观对国内外垃圾回收循环利用实例,特别是我国在电子垃圾处理方面的举措进行了认真分析和阐述,提出以循环经济、资源的利用回收解决环境问题的具体措施和建议。     

Biological pretreatment of Yellow River water

Bio-ceramic filter(BF) and moving-bed biofilm reactor(MBBR) were used for biological pretreatment of Yellow River water in this study. The BF only had slight advantage over MBBR for TOC and ammonia removal. However, like UV254, the average removal rate of THMFP in the BF was much higher than that in the MBBR. UV254 removal did not show obvious correlation with trihalomethane formation potential(THMFP) removal. Hexachlorocyclohexane could be effectively removed in both BF and MBBR. As for diatom and cyanobateria removal the MBBR had better performance than the BF, which was contrary to the average chlorophyll-a(Chl-a) removal rate. The proposal was made in this study that biological flocculation and sedimentation of sloughed biofilm should play a more important role on algae removal in the MBBR than in the BF. The BF and MBBR could effectively remove microcystins. Moreover, MBBR could be a promising technology for biological pretreatment.     

青藏高原生态资产地域划分中的SOFM网络技术

针对目前地域划分中存在的问题,论文尝试以人工神经网络技术作为区划工作的理论支撑,构建了自组织特征映射SOFM网络,以青藏高原环境与生态系统资产作为待分客体,探索了新技术和方法在生态资产地域划分中的应用。结果表明,对于自然界中广泛存在的非线性问题,SOFM网络具有比聚类分析等线性分类器更强的适应性。应用SOFM网络在对待分客体生态资产进行类型划分的基础上,使用策略性循环尺度转换(SCS)范式对其进行了区域转换,最终完成了青藏高原范围内生态资产的地域划分。     

上海合流污水深海排放强化一级预处理的研究

复合式厌氧污泥床反应器是一种改进的厌氧处理工艺 ,可有效去除城市生活污水中的污染物 ,并提高了污水的可生化性 ,是一种较理想的城市污水强化一级处理工艺 ,为上海合流污水深海排放的实施提供了保障。本文对该工艺的装置特点和处理效果进行了分析研究 ,并对其应用前景进行了展望。     

Fe(Ⅲ,Ⅱ)/H2O2体系中Fe(Ⅲ)水解特征的对比

利用Fe Ferron逐时络合比色法对类Fenton与Fenton体系中Fe(Ⅲ )水解形态的转化规律进行了比较 .结果表明 ,水解度越高 ,两体系中Fe(Ⅲ )的水解速度也越快 ,但水解度相同时 ,与Fenton体系相比 ,类Fenton反应生成的Fe(Ⅲ )的水解速率要低 ,且Feb 所占比例也较少 .与Fenton体系一致 ,类Fenton体系中的Fe(Ⅲ )水解速率随H2 O2 浓度的增加而减缓     

天津地区表层土壤多环芳烃含量的中尺度空间结构特征

应用地统计学技术对全天津地区表层土壤中 16种优控多环芳烃含量和土壤理化参数进行了空间结构分析 .结果显示 ,各组分浓度均存在中尺度的空间自相关性 .多环芳烃浓度的空间结构存在明显的各向异性 .大气运移和土壤TOC含量可能是影响土壤多环芳烃浓度空间结构特征的重要环境因素 .     

魔芋葡甘聚糖在污水处理中的应用

该文就魔芋葡甘聚糖的发展研究状况作了概述，并探讨其与蛋白质共混胶应用于水处理的可能性。     

滇池二维分层水质模拟研究

将三维问题“二维化”的分层迭代计算方法引入滇池水质模拟中，建立了湖泊二维分层水质模型，对滇池流场和总氮浓度场分两层进行了模拟计算，计算结果表明，该模型应用于滇池是成功的。     

含硫酸盐高浓度有机废水预处理的试验研究

在含硫酸盐高浓度有机废水浸泡铁刨花的静态试验的基础上，进行了“铁床”处理高浓度糖厂生产废水的动态试验。通过稳定工况之后，“铁床”CODcr平均下降41．3％，SO4^2-平均下降56．2％，有利于后续厌氧生物处理，并达到以废治废的目的。     

Application of Bayesian regularized BP neural network model for analysis of aquatic ecological data-A case study of chlorophyll-a prediction in Nanzui water area of Dongting Lake

Bayesian regularized BP neural network（BRBPNN） technique was applied in the chlorophyll-α prediction of Nanzui water area in Dongting Lake. Through BP network interpolation method, the input and output samples of the network were obtained. After the selection of input variables using stepwise/multiple linear regression method in SPSS i1.0 software, the BRBPNN model was established between chlorophyll-α and environmental parameters, biological parameters. The achieved optimal network structure was 3-11-1 with the correlation coefficients and the mean square errors for the training set and the test set as 0.999 and 0.000？8426, 0.981 and 0.0216 respectively. The sum of square weights between each input neuron and the hidden layer of optimal BRBPNN models of different structures indicated that the effect of individual input parameter on chlorophyll- α declined in the order of alga amount 〉 secchi disc depth（SD） 〉 electrical conductivity （EC）. Additionally, it also demonstrated that the contributions of these three factors were the maximal for the change of chlorophyll-α concentration, total phosphorus（TP） and total nitrogen（TN） were the minimal. All the results showed that BRBPNN model was capable of automated regularization parameter selection and thus it may ensure the excellent generation ability and robustness. Thus, this study laid the foundation for the application of BRBPNN model in the analysis of aquatic ecological data（chlorophyll-α prediction） and the explanation about the effective eutrophication treatment measures for Nanzui water area in Dongting Lake.